MLOps Academy · Lesson

Stages: Ingest, Prep, Train, Eval

Break training into clear, cacheable steps.

From One Big Script to Stages

A single train.py that does everything is hard to reuse and slow to debug. Splitting it into stages makes each step clear and independently runnable. 🧩

The Four Classic Stages

Most training pipelines follow the same shape: ingest, prep, train, eval. Each stage takes inputs and produces outputs the next one reads.

All lessons in this course

  1. Stages: Ingest, Prep, Train, Eval
  2. Define a Pipeline with DVC Stages
  3. Cache and Skip Unchanged Steps
  4. Parameterize Runs with params.yaml
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